Impulse noise cancellation of medical images using wavelet networks and median filters

Journal of Medical Signals and Sensors

Volumn 2, Issue 1, 2012, Pages 25-37

  Sadri, Amir Reza ^a   Zekri, Maryam ^b,c   Sadri, Saeid ^b,c   Gheissari, Niloofar ^a  

^a ISFAHAN UNIVERSITY OF TECHNOLOGY   (Iran)

^b Department of Electrical and Engineering ^*  (Iran)

^c ISFAHAN UNIVERSITY OF MEDICAL SCIENCES   (Iran)

Author keywords

Average background difference; gray level difference; impulse noise; wavelet network

Indexed keywords

EID: 84985925765     PISSN: None     EISSN: 22287477     Source Type: Journal    
DOI: 10.4103/2228-7477.108141     Document Type: Article

References (30)

1. Xue-jun Z, Hong G, Yun-ting Z, Ying L, Li G. Educational practice of computer science in medical imaging. IEEE Proceeding. Education Technology and Computer Science. vol. 3. 2010. p. 546-9.
2. Gravel P, Beaudoin G, De Guise JA. A method for modeling noise in medical images. IEEE Trans Med Imaging 2004;23:1221-31.
3. Abreu E, Lightstone M, Mitra SK, Arakawa K. A New efficient approach for the removal of impulse noise from highly corrupted images. IEEE Trans Image Process 1996;5:1012-25.
4. Rytsar YB, Ivasenko IB. Application of (alpha, beta)-trimmed mean filtering for removal of additive noise from images. SPIE Proceeding. Optoelectronic and Hybrid Optical/Digital Systems for Image Processing; 1997, p. 45-52.
5. Sawant A, Zeman H, Muratone D, Samant S, DiBianca F. Adaptive median filter algorithm to remove impulse noise in X-ray and CT images and speckle in ultrasound images. SPIE Proceeding Medical Imaging; 1999, p. 1263-74.
6. Chunhui Z, Qingbin X, Wei N. Study on the noise attenuation characteristics of generalized morphological filters. SPIE Proceeding Medical Imaging; 1998, p. 236-9.
7. Runtao D, Venetsanopoulos A. Generalized homomorphic and adaptive order statistic filters for the removal of impulsive and signal dependent noise. IEEE Trans Circuits Syst 2003;34:948-55.
8. Karthikeyan K, Chandrasekar C. Speckle Noise Reduction of Medical Ultrasound Images using Bayesshrink Wavelet Threshold. Int J Comput Appl 2011;22:8-14.
9. Wang L, Lu J, Li Y, Yahagi T, Okamoto T. Noise reduction using wavelet with application to medical X-ray image. International Conference on Industrial Technology, vol. 20, 2005. p. 33-8.
10. Cheng Y, Li Y, Xue D. Image Denoising Method Based on Curvelet Cycle Spinning, International Conference on Wireless Communications, Networking and Mobile Computing, vol. 13, 2008. pp. 1-3.
11. Russo F, Ramponi F. A Fuzzy filter for images corrupted by impulse noise. IEEE Trans Image Process 2000;3:168-70.
12. Anisha K, Wilscy M. Impulse noise removal from medical images using fuzzy genetic algorithm. Int J Multimed Appl 2011;3:93-106.
13. Astola J, Haavisto P, Neuovo Y. Vector median filters. IEEE Proceeding Image Processing, vol 78. 1990, p. 678-89.
14. Liang SF, Lu SM, Chang JY, Lin CT. A Novel two-stage impulse noise removal technique based on neural networks and fuzzy decision. IEEE Trans Fuzzy Syst 2008;16:863-73.
15. Hore JE, Qiu B, Wu HR. Improved color image vector filtering using fuzzy noise detection. Opt Eng 2003;42:1656-64.
16. Pati YC, Krishnaprasd PS. Analysis and synthesis of feed-forward neural networks using discrete affine wavelet transformations. IEEE Trans Neural Netw 1993;41:73-5.
17. Zhang QH, Benveniste A. Wavelet networks. IEEE Trans Neural Netw 1992;3:889-98.
18. Zhang QH. Using wavelet network in nonparametric estimation. IEEE Trans Signal Process 1997;8:227-36.
19. Oussar Y, Dreyfus G. Initialization by selection for wavelet network training. Neurocomput 2000;34:131-43.
20. Lien C, Huang C, Chen P, Lin Y. An efficient denoising architecture for removal of impulse noise in images. IEEE Trans Comput 2012;2:351-60.
21. Sulamiman SN, Isa N. Denoising-based clustering algorithms for segmentation of low level salt-and-pepper noise-corrupted images. IEEE Consum Electron 2011;56:2702-10.
22. Toh K, Isa N. Noise Adaptive fuzzy switching median filter for salt-and-pepper noise reduction. IEEE Trans Signal Process 2010;17:281-4.
23. Jiang X. Iterative truncated arithmetic mean filter and its properties. IEEE Trans Image Process 2012;21:1-11.
24. Galvao R, Becerra VM, Calado MF. Linear-wavelet networks. Int J Appl Math Comput Sci 2004:14:221-32.
25. Billings SA, Wei HL. A new class of wavelet networks for nonlinear system identification. IEEE Trans Neural Netw 2005;16:862-74.
26. Yilmaz S, Oysal Y. Fuzzy wavelet neural network models for prediction and identification of dynamical systems. IEEE Trans Neural Netw 2010;21:1599-609.
27. Duncan M. Engineering concepts on Ice. Available from: http://www.spectro.com/pages/e/p0105.htm. [Last accessed on 2010 Oct 25].
28. Kwan BY, Kwan HK. Impulse noise reduction in brain magnetic resonance imaging using fuzzy filters. World Acad Sci Eng Technol 2011;60:1194-7.
29. Silveria M, Nascimento JC, Marques JS, Maral AR, Mendona T, Yamauchi S, et al. Comparison of segmentation methods for melanoma diagnosis in dermoscopy images,. IEEE Trans Signal Process 2009;3:35-45.
30. Available from: http://www.cui.unige.ch/~svolos/SIP/ImageDenoising/Bernoulli/Image DenoisingBernoulli.html. [Last accessed on 2003 Jul 08].